A clinical approach to inherited hypertrophy: the use of family history in diagnosis, risk assessment, and management.
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ABSTRACT:
SUBMITTER: Dunn KE
PROVIDER: S-EPMC3898734 | biostudies-literature | 2013 Feb
REPOSITORIES: biostudies-literature
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A clinical approach to inherited hypertrophy: the use of family history in diagnosis, risk assessment, and management.
Dunn Kyla E KE Caleshu Colleen C Cirino Allison L AL Ho Carolyn Y CY Ashley Euan A EA
Circulation. Cardiovascular genetics 20130201 1
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Project description:BACKGROUND:Studies have shown that the quality of family health history (FHH) collection in primary care is inadequate to assess disease risk. To use FHH for risk assessment, collected data must have adequate detail. To address this issue, we developed a patient facing FHH assessment tool, MeTree. In this paper we report the content and quality of the FHH collected using MeTree. METHODS: DESIGN:A hybrid implementation-effectiveness study. Patients were recruited from 2009 to 2012. SETTING:Two community primary care clinics in Greensboro, NC. PARTICIPANTS:All non-adopted adult English speaking patients with upcoming appointments were invited to participate. INTERVENTION:Education about and collection of FHH with entry into MeTree. MEASURES:We report the proportion of pedigrees that were high-quality. High-quality pedigrees are defined as having all the following criteria: (1) three generations of relatives, (2) relatives' lineage, (3) relatives' gender, (4) an up-to-date FHH, (5) pertinent negatives noted, (6) age of disease onset in affected relatives, and for deceased relatives, (7) the age and (8) cause of death (Prim Care31:479-495, 2004.). RESULTS:Enrollment: 1,184. Participant demographics: age range 18-92 (mean 58.8, SD 11.79), 56% male, and 75% white. The median pedigree size was 21 (range 8-71) and the FHH entered into MeTree resulted in a database of 27,406 individuals. FHHs collected by MeTree were found to be high quality in 99.8% (N = 1,182/1,184) as compared to <4% at baseline. An average of 1.9 relatives per pedigree (range 0-50, SD 4.14) had no data reported. For pedigrees where at least one relative has no data (N = 497/1,184), 4.97 relatives per pedigree (range 1-50, SD 5.44) had no data. Talking with family members before using MeTree significantly decreased the proportion of relatives with no data reported (4.98% if you talked to your relative vs. 10.85% if you did not, p-value < 0.001.). CONCLUSION:Using MeTree improves the quantity and quality of the FHH data that is collected and talking with relatives prior to the collection of FHH significantly improves the quantity and quality of the data provided. This allows more patients to be accurately risk stratified and offered appropriate preventive care guided by their risk level. TRIAL NUMBER:NCT01372553.
| S-EPMC3937044 | biostudies-literature
Project description:BackgroundFamily history (FH) assessment is useful in identifying and managing patients at increased risk for cancer. This study assessed reported FH quality and associations with physician perceptions.MethodsPrimary care physicians practicing in two northeastern U.S. states were surveyed (n = 880; 70% response rate). Outcome measures of FH quality were extent of FH taken and ascertaining age at cancer diagnosis for affected family members. Predictors of quality measured in this survey included: perceived advantages and disadvantages of collecting FH information, knowledge of management options, access to supportive resources, and confidence in ability to interpret FH.ResultsReported collection of information regarding second degree blood relatives and age of diagnosis among affected relatives was low. All hypothesized predictors were associated with measures of FH quality, but not all were consistent independent predictors. Perceived advantages of taking a family history, access to supportive resources, and confidence in ability to identify and manage higher risk patients were independent predictors of both FH quality measures. Perceived disadvantages of taking a family history was independently associated one measure of FH quality. Knowledge of management options was not independently associated with either quality measure.ConclusionsModifiable perception and resource factors were independently associated with quality of FH taking in a large and diverse sample of primary care physicians. Improving FH quality for identification of high risk individuals will require multi-faceted interventions.
| S-EPMC2898682 | biostudies-literature
Project description:BackgroundThe presence of hereditary cancer syndromes in cancer patients can have an impact on current clinical care and post-treatment prevention and surveillance measures. Several barriers inhibit identification of hereditary cancer syndromes in routine practice. This paper describes the impact of using a patient-facing family health history risk assessment platform on the identification and referral of breast cancer patients to genetic counselling services.MethodsThis was a hybrid implementation-effectiveness study completed in breast cancer clinics. English-literate patients not previously referred for genetic counselling and/or gone through genetic testing were offered enrollment. Consented participants were provided educational materials on family health history collection, entered their family health history into the platform and completed a satisfaction survey. Upon completion, participants and their clinicians were given personalized risk reports. Chart abstraction was done to identify actions taken by patients, providers and genetic counsellors.ResultsOf 195 patients approached, 102 consented and completed the study (mean age 55.7, 100 % women). Sixty-six (65 %) met guideline criteria for genetic counseling of which 24 (36 %) were referred for genetic counseling. Of those referred, 13 (54 %) participants attended and eight (33 %) completed genetic testing. On multivariate logistic regression, referral was not associated with age, cancer stage, or race but was associated with clinical provider (p = 0.041). Most providers (71 %) had higher referral rates during the study compared to prior. The majority of participants found the experience useful (84 %), were more aware of their health risks (83 %), and were likely to recommend using a patient-facing platform to others (69 %).Conclusions65 % of patients attending breast cancer clinics in this study are at-risk for hereditary conditions based on current guidelines. Using a patient-facing risk assessment platform enhances the ability to identify these patients systematically and with widespread acceptability and recognized value by patients. As only a third of at-risk participants received referrals for genetic counseling, further understanding barriers to referral is needed to optimize hereditary risk assessment in oncology practices.Trial registrationNIH Clinical Trials registry, NCT04639934 . Registered Nov 23, 2020 -- Retrospectively registered.
| S-EPMC7981979 | biostudies-literature
Project description:IntroductionResearch has shown that eating disorder (ED) patients who abuse substances demonstrate worse ED symptomatology and poorer outcomes than those with EDs alone, including increased general medical complications and psychopathology, longer recovery times, poorer functional outcomes and higher relapse rates. This article provides a broad overview of the prevalence, aetiology, assessment and management of co-morbid EDs and substance use disorders (SUDs).ReviewThe co-occurrence of EDs and SUDs is high. The functional relationship between EDs and SUDs vary within and across ED subtypes, depends on the class of substance, and needs to be carefully assessed for each patient. Substances such as caffeine, tobacco, insulin, thyroid medications, stimulants or over the counter medications (laxatives, diuretics) may be used to aid weight loss and/or provide energy, and alcohol or psychoactive substances could be used for emotional regulation or as part of a pattern of impulsive behaviour. A key message conveyed in the current literature is the importance of screening and assessment for co-morbid SUDs and EDs in patients presenting with either disorder. There is a paucity of treatment studies on the management of co-occurring EDs and SUDs. Overall, the literature indicates that the ED and SUD should be addressed simultaneously using a multi-disciplinary approach. The need for medical stabilization, hospitalization or inpatient treatment needs to be assessed based on general medical and psychiatric considerations. Common features across therapeutic interventions include psycho-education about the aetiological commonalities, risks and sequelae of concurrent ED behaviours and substance abuse, dietary education and planning, cognitive challenging of eating disordered attitudes and beliefs, building of skills and coping mechanisms, addressing obstacles to improvement and the prevention of relapse. Emphasis should be placed on building a collaborative therapeutic relationship and avoiding power struggles. Cognitive behavioural therapy has been frequently used in the treatment of co-morbid EDs and SUDs, however there are no randomized controlled trials. More recently evidence has been found for the efficacy of dialectical behavioural therapy in reducing both ED and substance use behaviours.ConclusionFuture research would benefit from a meta-analysis of the current research in order to better understand the relationships between these two commonly co-occurring disorders.
| S-EPMC4226257 | biostudies-literature
Project description:Background:Esophageal squamous cell carcinoma (ESCC) is a common malignant tumor with significant geographical variation and familial aggregation. However, the potentially different mechanisms underlying tumorigenesis in patients with ESCC with and without a family history of the disease remain unclear. In this study, the genes mutated in familial and nonfamilial ESCC were analyzed. Further, we aimed to explore the genes related to ESCC and attempt to identify potential patients in families with a history of ESCC. Methods:Next-generation sequencing technology was used to examine germline mutations and mutation profiles in 36 matched tumor-normal ESCC specimens. Additionally, tumor mutational burden (TMB) values were measured in two cohorts. Results:We identified four novel germline mutations in patients with familial ESCC, in BAX (c.121dupG: p.E41G), CDKN2A (c.374dupA: p.D125E), TP53 (c.856G>A: p.E286K), and CHEK1 (c.923+1G>A). Mutation profiles revealed that patients with and without a family history of ESCC had similar high-frequency gene mutation profiles, among which TP53 was the most commonly mutated gene. Additionally, tumor-specific mutated genes in patients with a positive family history of ESCC were APC, AKT3, DPYD, EP300, NFE2L2, PPP2R1A, RUNX1, and VEGFA, while those in patients without a family history of ESCC were CXCR4, PIK3R2, SMARCA4, and TTF1. Moreover, patients with positive family history had significantly higher TMB values (7.8 ± 4.1 vs 5.0 ± 2.4, for patients with and without a family history, respectively; P = 0.038). Conclusion:Our results identified mutation profiles in patients with familial and nonfamilial ESCC, and identified germline mutations in patients with positive history. TMB values may be informative for immunotherapy approaches in familial ESCC.
| S-EPMC7481280 | biostudies-literature
Project description:Identification of new small molecules that regulate the step-wise differentiation of hPSC into dopaminergic neurons population. Furthermore, the naturally occurring steroid, guggulsterone, was found to be the most effective inducer of neural stem cells into dopaminergic neurons.
2013-04-24 | GSE42265 | GEO
Project description:Identification of new small molecules that regulate the step-wise differentiation of hPSC into dopaminergic neurons population. Furthermore, the naturally occurring steroid, guggulsterone, was found to be the most effective inducer of neural stem cells into dopaminergic neurons. Total RNA extracted at different stages of neural differentiation from human pluripotent stem cells
2013-04-24 | E-GEOD-42265 | biostudies-arrayexpress
Project description:BackgroundElectronic health records store large amounts of patient clinical data. Despite efforts to structure patient data, clinical notes containing rich patient information remain stored as free text, greatly limiting its exploitation. This includes family history, which is highly relevant for applications such as diagnosis and prognosis.ObjectiveThis study aims to develop automatic strategies for annotating family history information in clinical notes, focusing not only on the extraction of relevant entities such as family members and disease mentions but also on the extraction of relations between the identified entities.MethodsThis study extends a previous contribution for the 2019 track on family history extraction from national natural language processing clinical challenges by improving a previously developed rule-based engine, using deep learning (DL) approaches for the extraction of entities from clinical notes, and combining both approaches in a hybrid end-to-end system capable of successfully extracting family member and observation entities and the relations between those entities. Furthermore, this study analyzes the impact of factors such as the use of external resources and different types of embeddings in the performance of DL models.ResultsThe approaches developed were evaluated in a first task regarding entity extraction and in a second task concerning relation extraction. The proposed DL approach improved observation extraction, obtaining F1 scores of 0.8688 and 0.7907 in the training and test sets, respectively. However, DL approaches have limitations in the extraction of family members. The rule-based engine was adjusted to have higher generalizing capability and achieved family member extraction F1 scores of 0.8823 and 0.8092 in the training and test sets, respectively. The resulting hybrid system obtained F1 scores of 0.8743 and 0.7979 in the training and test sets, respectively. For the second task, the original evaluator was adjusted to perform a more exact evaluation than the original one, and the hybrid system obtained F1 scores of 0.6480 and 0.5082 in the training and test sets, respectively.ConclusionsWe evaluated the impact of several factors on the performance of DL models, and we present an end-to-end system for extracting family history information from clinical notes, which can help in the structuring and reuse of this type of information. The final hybrid solution is provided in a publicly available code repository.
| S-EPMC7803476 | biostudies-literature
Project description:With the advent of high throughput sequencing, the identification of genetic causes of cardiovascular disease (CVD) has become an integral part of medical diagnosis and management and at the forefront of personalized medicine in this field. The use of whole exome sequencing for clinical diagnosis, risk stratification, and management of inherited CVD has not been previously evaluated. We analyzed the results of whole exome sequencing in first 200 adult patients with inherited CVD, who underwent genetic testing at the Yale Program for Cardiovascular Genetics. Genetic diagnosis was reached and reported with a success rate of 26.5% (53 of 200 patients). This compares to 18% (36 of 200) that would have been diagnosed using commercially available genetic panels (P=0.04). Whole exome sequencing was particularly useful for clinical diagnosis in patients with aborted sudden cardiac death, in whom the primary insult for the presence of both depressed cardiac function and prolonged QT had remained unknown. The analysis of the remaining cases using genome annotation and disease segregation led to the discovery of novel candidate genes in another 14% of the cases. Whole exome sequencing is an exceptionally valuable screening tool for its capability to establish the clinical diagnosis of inherited CVDs, particularly for poorly defined cases of sudden cardiac death. By presenting novel candidate genes and their potential disease associations, we also provide evidence for the use of this genetic tool for the identification of novel CVD genes. Creation and sharing of exome databases across centers of care should facilitate the discovery of unknown CVD genes.
| S-EPMC5245580 | biostudies-literature
Project description:Inherited thrombocytopenias have been considered exceedingly rare for a long time, but recent advances have facilitated diagnosis and greatly enabled the discovery of new causative genes. MYH9-related disease (MYH9-RD) represents one of the most frequent forms of inherited thrombocytopenia, usually presenting with nonspecific clinical manifestations, which renders it difficult to establish an accurate diagnosis. MYH9-RD is an autosomal dominant-inherited thrombocytopenia caused by deleterious variants in the MYH9 gene encoding the heavy chain of nonmuscle myosin IIA. Patients with MYH9-RD usually present with thrombocytopenia and platelet macrocytosis at birth or in infancy, and most of them may develop one or more extrahematologic manifestations of progressive nephritis, sensorial hearing loss, presenile cataracts, and elevated liver enzymatic levels during childhood and adult life. Here, we have reviewed recent advances in the study of MYH9-RD, which aims to provide an updated and comprehensive summary of the current knowledge and improve our understanding of the genetic spectrum, underlying mechanisms, clinical phenotypes, diagnosis, and management approaches of this rare disease. Importantly, our goal is to enable physicians to better understand this rare disease and highlight the critical role of genetic etiologic analysis in ensuring accurate diagnosis, clinical management, and genetic counseling while avoiding ineffective and potentially harmful therapies for MYH9-RD patients.
| S-EPMC11415342 | biostudies-literature